Research Papers

Markov/CCMT Dynamic Reliability Analysis of the Main and Startup Feedwater Control System in Nuclear Power Plant

[+] Author and Article Information
Wentao Li

Shanghai Nuclear Engineering Research &
Design Institute Co. Ltd.,
No. 29 Hongcao Road,
Shanghai 200233, China
e-mail: liwentao@snerdi.com.cn

Danying Gu

Shanghai Nuclear Engineering Research &
Design Institute Co., Ltd,
No. 29 Hongcao Road,
Shanghai 200233, China
e-mail: Gudanying@snerdi.com.cn

Henan Zhang

Shanghai Nuclear Engineering Research &
Design Institute Co. Ltd,
No. 29 Hongcao Road,
Shanghai 200233, China
e-mail: zhanghenan@snerdi.com.cn

Manuscript received November 8, 2017; final manuscript received June 25, 2018; published online September 10, 2018. Assoc. Editor: John F. P. de Grosbois.

ASME J of Nuclear Rad Sci 4(4), 041011 (Sep 10, 2018) (5 pages) Paper No: NERS-17-1290; doi: 10.1115/1.4040888 History: Received November 08, 2017; Revised June 25, 2018

The dynamic reliability of the main and startup feedwater control system in nuclear power plant is evaluated by conducting the Markov cell-to-cell mapping technology (Markov/CCMT) methodology. All the equipment failure modes and potential failure states within the system are analyzed. This process illustrates the uncertainty in the physical process of the system. Furthermore, the failure probability and cut-set of the system can be computed to provide a more comprehensive and accurate response to the system characteristics and reflect the two types of interaction within the system. In contrast to the traditional static probability safety assessment, the Markov/CCMT methodology remedies the defect in terms of event sequence setting, control loop, multiple top event competition, uncertainty of the analysis result, as well as the insufficient analysis of human-caused failure. The reliability analysis of the main and startup feedwater control system (FWCS) based on the self-developed Markov/CCMT reliability analysis software verifies the feasibility and engineering application value of the methodology and software.

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Grahic Jump Location
Fig. 1

Markov/CCMT model framework

Grahic Jump Location
Fig. 2

Digital feedwater control system model

Grahic Jump Location
Fig. 3

Probability distribution function of the top three state combinations

Grahic Jump Location
Fig. 4

Percentage of the top three state combinations



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